Temporal templates for detecting the trajectories of moving vehicles

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Abstract

In this study, we deal with the problem of detecting the trajectories of moving vehicles. We introduce a method, based on the spatio-temporal connectivity analysis, to extract the vehicles trajectories from temporal templates, spanned over a short period of time. Temporal templates are conformed with the successive images differences. The trajectories are computed using the centers of the blobs in the temporal template. A Kalman filter for a constant value with emphasis in the measurement uncertainty is used to smooth the result. The algorithm is tested extensively using a sequence took from tower overlooking a vehicular intersection. Our approach allow us to detect the vehicles trajectories without the need to construct a background model or using a sophisticated tracking strategy for the moving objects. Our experiments show that the scheme we propose is reliable, and fast. © 2009 Springer Berlin Heidelberg.

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Jiménez, H., & Salas, J. (2009). Temporal templates for detecting the trajectories of moving vehicles. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5807 LNCS, pp. 485–493). https://doi.org/10.1007/978-3-642-04697-1_45

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